Detailed analysis of captured phishing page
Used to detect similar phishing pages based on HTML content
| Algorithm | Hash Value |
|---|---|
|
CONTENT
TLSH
|
T1660405F11841B2378AD763915E39F71CF3D261D75D6266060EF0CA1BEA8BF819C1287A |
|
CONTENT
ssdeep
|
1536:sOwwazwmzwWzwTxzw4zwHzwywczwmzwWzwTxzw4zwHzwywF5zwmzwWzwTxzw4zww:s8paqsf7wFUbuwQY |
Used to detect visually similar phishing pages based on screenshots
| Algorithm | Hash Value |
|---|---|
|
VISUAL
pHash
|
b14c4e334e53576c |
|
VISUAL
aHash
|
00c3c3cfcfcfefff |
|
VISUAL
dHash
|
d01717989a9a9872 |
|
VISUAL
wHash
|
008381cfc3c7c7fb |
|
VISUAL
colorHash
|
06400000400 |
|
VISUAL
cropResistant
|
17179c9a9a989872,30d0d8f022e8e840,0100103232100001,0105113333110101,eff731795c561456 |
Victim enters username and password into fake login form. Credentials are captured via JavaScript and exfiltrated to attacker's server in real-time.
Malicious code is obfuscated using 4876 techniques to evade detection by security scanners and make reverse engineering more difficult.
Drainer supports multiple blockchain networks and checks for high-value tokens on each chain before executing drain operations.